fitsadC-class | R Documentation |

`"fitsadC"`

for maximum likelihood fitting of
species abundance distributions from data in abundance classesThis class extends `mle2-class`

to encapsulate models of species
abundance distributions (SADs) fitted by maximum likelihood, from data
where species are classified in abundance classes (e.g, histograms or
frequency tables of number of species in classes of abundances).

Objects can be created by calls of the form ```
new("fitsadC",
...)
```

, or, more commonly a call to functions `fitexpC`

,
`fitgammaC`

, `fitlnormC`

,
`fitparetoC`

, `fitweibullC`

, which fit a
probability distribution to a table of frequency of species
abundances.

`sad`

:Object of class

`"character"`

; root name of the species abundance distribution fitted. See man page of`fitsad`

for available models.`trunc`

:Object of class

`"numeric"`

; truncation value used in the fitted model. 'NA' for a non-truncated distribution.`hist`

:Object of class

`"histogram"`

; a table of frequencies of species in abundance classes, returned by the function`hist`

.`call`

:Object of class

`"language"`

; The call to`mle2`

.`call.orig`

:Object of class

`"language"`

The call to`mle2`

, saved in its original form (i.e. without data arguments evaluated).`coef`

:Object of class

`"numeric"`

; Vector of estimated parameters.`fullcoef`

:Object of class

`"numeric"`

; Fixed and estimated parameters.`vcov`

:Object of class

`"matrix"`

; Approximate variance-covariance matrix, based on the second derivative matrix at the MLE.`min`

:Object of class

`"numeric"`

; Minimum value of objective function = minimum negative log-likelihood.`details`

:Object of class

`"list"`

; Return value from`optim`

.`minuslogl`

:Object of class

`"function"`

; The negative log-likelihood function.`method`

:Object of class

`"character"`

; The optimization method used.`data`

:Object of class

`"data.frame"`

; Data with which to evaluate the negative log-likelihood function.`formula`

:Object of class

`"character"`

; If a formula was specified, a character vector giving the formula and parameter specifications.`optimizer`

:Object of class

`"character"`

; The optimizing function used.

Class `"mle2"`

, directly.

- coverpred
`signature(object = "fitsadC", sad = "missing", coef = "missing", trunc = "missing", breaks = "missing", mids = "missing", S = "missing")`

: predicted number of species in each abundance class see`coverpred`

- nobs
`signature(object = "fitsadC")`

: Displays number of observations (number of species) in the data to which the model was fitted.- plot
`signature(x = "fitsadC", y = "ANY")`

: diagnostic plots of the fitted model.- ppsad
`signature(x = "fitsadC", sad = "missing", coef = "missing", trunc = "missing")`

: plot of observed vs predicted percentiles of the abundance distribution, details in`ppsad`

.- qqsad
`signature(x = "fitsadC", sad = "missing", coef = "missing", trunc = "missing", distr = "missing")`

: plot of observed vs predicted quantiles of the abundance distribution, details in`qqsad.`

- radpred
`signature(object = "fitsadC", sad = "missing", rad = "missing", coef = "missing", trunc = "missing", distr = "missing", S = "missing", N = "missing")`

: expected abundances of the 1st to n-th most abundant species, see`rad`

and`radpred`

.- show
`signature(object = "fitsadC")`

: Displays object.

Class `fitsadC`

only adds three slots to class
`mle2`

. The descriptions of slots inherited from `mle2-class`

replicate those in `mle2-class`

.

Paulo I Prado prado@ib.usp.br, after Ben Bolker and R Core Team.

this class builds on `mle2-class`

of bbmle package (Bolker
2012), which in turn builds on `mle-class`

.

Bolker, B. and R Development Core Team 2012. bbmle: Tools for general maximum likelihood estimation. R package version 1.0.5.2. http://CRAN.R-project.org/package=bbmle

`mle2-class`

for all methods available from which
`fitsadC-class`

inherits; `fitsadC`

for details on
fitting SADs models from frequency tables; `coverpred`

to
get frequencies of species in abundances classes predicted
from fitted models.

```
## Example of fitting a sad model to cover data
## Abundance classes: cover scale for plants
Lbrk <- c(0,1,3,5,15,25,35,45,55,65,75,85,95,100)
## To fit a sad model to cover data, data sould be in histogram format
grass.h <- hist(grasslands$mids, breaks = Lbrk, plot = FALSE)
class(grass.h) ## class "histogram"
## Fits a Pareto distribution to the histogram object
grass.p <- fitparetoC(grass.h)
class(grass.p)
## The class has a plot method to show diagnostic plots
par(mfrow=c(2,2))
plot(grass.p)
par(mfrow=c(1,1))
## Some methods inherited form mle2-class
summary(grass.p)
coef(grass.p)
AIC(grass.p)
```

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.